Regional Distribution of Carbon Intensity and its Driving Factors in China: An Empirical Study Based on Provincial Data
文献类型：期刊论文
| 作者 | Wu, Rongwei1,2; Dong, Jiefang3; Zhou, Liang4,5; Zhang, Lu1,2 |
| 刊名 | POLISH JOURNAL OF ENVIRONMENTAL STUDIES
 |
| 出版日期 | 2018 |
| 卷号 | 27期号:3页码:1331-1341 |
| 关键词 | carbon intensity Gini coefficient panel date analysis FGLS China |
| ISSN号 | 1230-1485 |
| DOI | 10.15244/pjoes/76364 |
| 通讯作者 | Zhou, Liang(zhougeo@126.com) |
| 英文摘要 | The regional distribution and driving factors of total carbon emissions have been the focus of considerable research. However, carbon intensity rather than total carbon emissions has been selected as the emissions reduction index in China. The Chinese government has committed to reducing carbon intensity by 60-65% from 2005 levels. Currently, limited academic attention has been given to the regional distribution and driving factors of carbon intensity. To explore the means of achieving the carbon intensity target in China, Gini coefficients were employed in this paper to investigate regional differences in carbon intensity across 30 provinces from 1995 to 2014. Moreover, the FGLS (feasible generalized least squares) method was applied to identify the key influencing factors of carbon intensity at the national and three regional levels. The results indicate that: 1. Chinese inter-provincial Gini coefficients of carbon intensity have increased steadily in recent years, which indicates that the difference in carbon intensity between provinces in China has widened. 2. Economic growth, foreign direct investment, and trade openness were negatively correlated with carbon intensity. Conversely, coal consumption, industrial proportion, and urbanization were positively correlated with carbon intensity. Moreover, urbanization has proven to be the most important factor affecting China's carbon intensity. 3. The dominant cause of carbon intensity varies by region. In particular, the dominant cause of carbon intensity in low-and medium-level regions is urbanization. However, the dominant cause of carbon intensity in high-level regions is coal consumption. 4. Based on these empirical findings, policy recommendations to reduce carbon intensity were proposed. In summary, the improvement of urbanization quality in both low-and medium-level regions is urgently needed. However, optimizing the energy structure is essential to carbon intensity reduction in high-level regions. |
| WOS关键词 | ENERGY-CONSUMPTION ; DIOXIDE EMISSIONS ; CO2 EMISSIONS ; PANEL-DATA ; CONVERGENCE ; DECOMPOSITION ; URBANIZATION ; DYNAMICS ; POLICY ; LEAD |
| 资助项目 | Grant Program of Clean Development Mechanism Fund of China[2014092] ; Chinese Postdoctoral Science Foundation[2016M600121] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000427520400039 |
| 出版者 | HARD |
| 资助机构 | Grant Program of Clean Development Mechanism Fund of China ; Chinese Postdoctoral Science Foundation |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/57206]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhou, Liang |
| 作者单位 | 1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Yuncheng Univ, Dept Econ & Management, Yuncheng 044000, Peoples R China 4.Lanzhou Jiaotong Univ, Fac Geomat, Lanzhou 730070, Gansu, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Rongwei,Dong, Jiefang,Zhou, Liang,et al. Regional Distribution of Carbon Intensity and its Driving Factors in China: An Empirical Study Based on Provincial Data[J]. POLISH JOURNAL OF ENVIRONMENTAL STUDIES,2018,27(3):1331-1341. |
| APA | Wu, Rongwei,Dong, Jiefang,Zhou, Liang,&Zhang, Lu.(2018).Regional Distribution of Carbon Intensity and its Driving Factors in China: An Empirical Study Based on Provincial Data.POLISH JOURNAL OF ENVIRONMENTAL STUDIES,27(3),1331-1341. |
| MLA | Wu, Rongwei,et al."Regional Distribution of Carbon Intensity and its Driving Factors in China: An Empirical Study Based on Provincial Data".POLISH JOURNAL OF ENVIRONMENTAL STUDIES 27.3(2018):1331-1341. |
入库方式： OAI收割
来源：地理科学与资源研究所
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